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1.  Gene-Lifestyle Interaction and Type 2 Diabetes: The EPIC InterAct Case-Cohort Study 
PLoS Medicine  2014;11(5):e1001647.
In this study, Wareham and colleagues quantified the combined effects of genetic and lifestyle factors on risk of T2D in order to inform strategies for prevention. The authors found that the relative effect of a type 2 diabetes genetic risk score is greater in younger and leaner participants, and the high absolute risk associated with obesity at any level of genetic risk highlights the importance of universal rather than targeted approaches to lifestyle intervention.
Please see later in the article for the Editors' Summary
Background
Understanding of the genetic basis of type 2 diabetes (T2D) has progressed rapidly, but the interactions between common genetic variants and lifestyle risk factors have not been systematically investigated in studies with adequate statistical power. Therefore, we aimed to quantify the combined effects of genetic and lifestyle factors on risk of T2D in order to inform strategies for prevention.
Methods and Findings
The InterAct study includes 12,403 incident T2D cases and a representative sub-cohort of 16,154 individuals from a cohort of 340,234 European participants with 3.99 million person-years of follow-up. We studied the combined effects of an additive genetic T2D risk score and modifiable and non-modifiable risk factors using Prentice-weighted Cox regression and random effects meta-analysis methods. The effect of the genetic score was significantly greater in younger individuals (p for interaction  = 1.20×10−4). Relative genetic risk (per standard deviation [4.4 risk alleles]) was also larger in participants who were leaner, both in terms of body mass index (p for interaction  = 1.50×10−3) and waist circumference (p for interaction  = 7.49×10−9). Examination of absolute risks by strata showed the importance of obesity for T2D risk. The 10-y cumulative incidence of T2D rose from 0.25% to 0.89% across extreme quartiles of the genetic score in normal weight individuals, compared to 4.22% to 7.99% in obese individuals. We detected no significant interactions between the genetic score and sex, diabetes family history, physical activity, or dietary habits assessed by a Mediterranean diet score.
Conclusions
The relative effect of a T2D genetic risk score is greater in younger and leaner participants. However, this sub-group is at low absolute risk and would not be a logical target for preventive interventions. The high absolute risk associated with obesity at any level of genetic risk highlights the importance of universal rather than targeted approaches to lifestyle intervention.
Please see later in the article for the Editors' Summary
Editors' Summary
Background
Worldwide, more than 380 million people currently have diabetes, and the condition is becoming increasingly common. Diabetes is characterized by high levels of glucose (sugar) in the blood. Blood sugar levels are usually controlled by insulin, a hormone released by the pancreas after meals (digestion of food produces glucose). In people with type 2 diabetes (the commonest type of diabetes), blood sugar control fails because the fat and muscle cells that normally respond to insulin by removing excess sugar from the blood become less responsive to insulin. Type 2 diabetes can often initially be controlled with diet and exercise (lifestyle changes) and with antidiabetic drugs such as metformin and sulfonylureas, but patients may eventually need insulin injections to control their blood sugar levels. Long-term complications of diabetes, which include an increased risk of heart disease and stroke, reduce the life expectancy of people with diabetes by about ten years compared to people without diabetes.
Why Was This Study Done?
Type 2 diabetes is thought to originate from the interplay between genetic and lifestyle factors. But although rapid progress is being made in understanding the genetic basis of type 2 diabetes, it is not known whether the consequences of adverse lifestyles (for example, being overweight and/or physically inactive) differ according to an individual's underlying genetic risk of diabetes. It is important to investigate this question to inform strategies for prevention. If, for example, obese individuals with a high level of genetic risk have a higher risk of developing diabetes than obese individuals with a low level of genetic risk, then preventative strategies that target lifestyle interventions to obese individuals with a high genetic risk would be more effective than strategies that target all obese individuals. In this case-cohort study, researchers from the InterAct consortium quantify the combined effects of genetic and lifestyle factors on the risk of type 2 diabetes. A case-cohort study measures exposure to potential risk factors in a group (cohort) of people and compares the occurrence of these risk factors in people who later develop the disease with those who remain disease free.
What Did the Researchers Do and Find?
The InterAct study involves 12,403 middle-aged individuals who developed type 2 diabetes after enrollment (incident cases) into the European Prospective Investigation into Cancer and Nutrition (EPIC) and a sub-cohort of 16,154 EPIC participants. The researchers calculated a genetic type 2 diabetes risk score for most of these individuals by determining which of 49 gene variants associated with type 2 diabetes each person carried, and collected baseline information about exposure to lifestyle risk factors for type 2 diabetes. They then used various statistical approaches to examine the combined effects of the genetic risk score and lifestyle factors on diabetes development. The effect of the genetic score was greater in younger individuals than in older individuals and greater in leaner participants than in participants with larger amounts of body fat. The absolute risk of type 2 diabetes, expressed as the ten-year cumulative incidence of type 2 diabetes (the percentage of participants who developed diabetes over a ten-year period) increased with increasing genetic score in normal weight individuals from 0.25% in people with the lowest genetic risk scores to 0.89% in those with the highest scores; in obese people, the ten-year cumulative incidence rose from 4.22% to 7.99% with increasing genetic risk score.
What Do These Findings Mean?
These findings show that in this middle-aged cohort, the relative association with type 2 diabetes of a genetic risk score comprised of a large number of gene variants is greatest in individuals who are younger and leaner at baseline. This finding may in part reflect the methods used to originally identify gene variants associated with type 2 diabetes, and future investigations that include other genetic variants, other lifestyle factors, and individuals living in other settings should be undertaken to confirm this finding. Importantly, however, this study shows that young, lean individuals with a high genetic risk score have a low absolute risk of developing type 2 diabetes. Thus, this sub-group of individuals is not a logical target for preventative interventions. Rather, suggest the researchers, the high absolute risk of type 2 diabetes associated with obesity at any level of genetic risk highlights the importance of universal rather than targeted approaches to lifestyle intervention.
Additional Information
Please access these websites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001647.
The US National Diabetes Information Clearinghouse provides information about diabetes for patients, health-care professionals and the general public, including detailed information on diabetes prevention (in English and Spanish)
The UK National Health Service Choices website provides information for patients and carers about type 2 diabetes and about living with diabetes; it also provides people's stories about diabetes
The charity Diabetes UK provides detailed information for patients and carers in several languages, including information on healthy lifestyles for people with diabetes
The UK-based non-profit organization Healthtalkonline has interviews with people about their experiences of diabetes
The Genetic Landscape of Diabetes is published by the US National Center for Biotechnology Information
More information on the InterAct study is available
MedlinePlus provides links to further resources and advice about diabetes and diabetes prevention (in English and Spanish)
doi:10.1371/journal.pmed.1001647
PMCID: PMC4028183  PMID: 24845081
2.  Genome-Wide Association Study Identifies a Novel Locus Contributing to Type 2 Diabetes Susceptibility in Sikhs of Punjabi Origin From India 
Diabetes  2013;62(5):1746-1755.
We performed a genome-wide association study (GWAS) and a multistage meta-analysis of type 2 diabetes (T2D) in Punjabi Sikhs from India. Our discovery GWAS in 1,616 individuals (842 case subjects) was followed by in silico replication of the top 513 independent single nucleotide polymorphisms (SNPs) (P < 10−3) in Punjabi Sikhs (n = 2,819; 801 case subjects). We further replicated 66 SNPs (P < 10−4) through genotyping in a Punjabi Sikh sample (n = 2,894; 1,711 case subjects). On combined meta-analysis in Sikh populations (n = 7,329; 3,354 case subjects), we identified a novel locus in association with T2D at 13q12 represented by a directly genotyped intronic SNP (rs9552911, P = 1.82 × 10−8) in the SGCG gene. Next, we undertook in silico replication (stage 2b) of the top 513 signals (P < 10−3) in 29,157 non-Sikh South Asians (10,971 case subjects) and de novo genotyping of up to 31 top signals (P < 10−4) in 10,817 South Asians (5,157 case subjects) (stage 3b). In combined South Asian meta-analysis, we observed six suggestive associations (P < 10−5 to < 10−7), including SNPs at HMG1L1/CTCFL, PLXNA4, SCAP, and chr5p11. Further evaluation of 31 top SNPs in 33,707 East Asians (16,746 case subjects) (stage 3c) and 47,117 Europeans (8,130 case subjects) (stage 3d), and joint meta-analysis of 128,127 individuals (44,358 case subjects) from 27 multiethnic studies, did not reveal any additional loci nor was there any evidence of replication for the new variant. Our findings provide new evidence on the presence of a population-specific signal in relation to T2D, which may provide additional insights into T2D pathogenesis.
doi:10.2337/db12-1077
PMCID: PMC3636649  PMID: 23300278
3.  Discovery and Refinement of Loci Associated with Lipid Levels 
Willer, Cristen J. | Schmidt, Ellen M. | Sengupta, Sebanti | Peloso, Gina M. | Gustafsson, Stefan | Kanoni, Stavroula | Ganna, Andrea | Chen, Jin | Buchkovich, Martin L. | Mora, Samia | Beckmann, Jacques S. | Bragg-Gresham, Jennifer L. | Chang, Hsing-Yi | Demirkan, Ayşe | Den Hertog, Heleen M. | Do, Ron | Donnelly, Louise A. | Ehret, Georg B. | Esko, Tõnu | Feitosa, Mary F. | Ferreira, Teresa | Fischer, Krista | Fontanillas, Pierre | Fraser, Ross M. | Freitag, Daniel F. | Gurdasani, Deepti | Heikkilä, Kauko | Hyppönen, Elina | Isaacs, Aaron | Jackson, Anne U. | Johansson, Åsa | Johnson, Toby | Kaakinen, Marika | Kettunen, Johannes | Kleber, Marcus E. | Li, Xiaohui | Luan, Jian’an | Lyytikäinen, Leo-Pekka | Magnusson, Patrik K.E. | Mangino, Massimo | Mihailov, Evelin | Montasser, May E. | Müller-Nurasyid, Martina | Nolte, Ilja M. | O’Connell, Jeffrey R. | Palmer, Cameron D. | Perola, Markus | Petersen, Ann-Kristin | Sanna, Serena | Saxena, Richa | Service, Susan K. | Shah, Sonia | Shungin, Dmitry | Sidore, Carlo | Song, Ci | Strawbridge, Rona J. | Surakka, Ida | Tanaka, Toshiko | Teslovich, Tanya M. | Thorleifsson, Gudmar | Van den Herik, Evita G. | Voight, Benjamin F. | Volcik, Kelly A. | Waite, Lindsay L. | Wong, Andrew | Wu, Ying | Zhang, Weihua | Absher, Devin | Asiki, Gershim | Barroso, Inês | Been, Latonya F. | Bolton, Jennifer L. | Bonnycastle, Lori L | Brambilla, Paolo | Burnett, Mary S. | Cesana, Giancarlo | Dimitriou, Maria | Doney, Alex S.F. | Döring, Angela | Elliott, Paul | Epstein, Stephen E. | Ingi Eyjolfsson, Gudmundur | Gigante, Bruna | Goodarzi, Mark O. | Grallert, Harald | Gravito, Martha L. | Groves, Christopher J. | Hallmans, Göran | Hartikainen, Anna-Liisa | Hayward, Caroline | Hernandez, Dena | Hicks, Andrew A. | Holm, Hilma | Hung, Yi-Jen | Illig, Thomas | Jones, Michelle R. | Kaleebu, Pontiano | Kastelein, John J.P. | Khaw, Kay-Tee | Kim, Eric | Klopp, Norman | Komulainen, Pirjo | Kumari, Meena | Langenberg, Claudia | Lehtimäki, Terho | Lin, Shih-Yi | Lindström, Jaana | Loos, Ruth J.F. | Mach, François | McArdle, Wendy L | Meisinger, Christa | Mitchell, Braxton D. | Müller, Gabrielle | Nagaraja, Ramaiah | Narisu, Narisu | Nieminen, Tuomo V.M. | Nsubuga, Rebecca N. | Olafsson, Isleifur | Ong, Ken K. | Palotie, Aarno | Papamarkou, Theodore | Pomilla, Cristina | Pouta, Anneli | Rader, Daniel J. | Reilly, Muredach P. | Ridker, Paul M. | Rivadeneira, Fernando | Rudan, Igor | Ruokonen, Aimo | Samani, Nilesh | Scharnagl, Hubert | Seeley, Janet | Silander, Kaisa | Stančáková, Alena | Stirrups, Kathleen | Swift, Amy J. | Tiret, Laurence | Uitterlinden, Andre G. | van Pelt, L. Joost | Vedantam, Sailaja | Wainwright, Nicholas | Wijmenga, Cisca | Wild, Sarah H. | Willemsen, Gonneke | Wilsgaard, Tom | Wilson, James F. | Young, Elizabeth H. | Zhao, Jing Hua | Adair, Linda S. | Arveiler, Dominique | Assimes, Themistocles L. | Bandinelli, Stefania | Bennett, Franklyn | Bochud, Murielle | Boehm, Bernhard O. | Boomsma, Dorret I. | Borecki, Ingrid B. | Bornstein, Stefan R. | Bovet, Pascal | Burnier, Michel | Campbell, Harry | Chakravarti, Aravinda | Chambers, John C. | Chen, Yii-Der Ida | Collins, Francis S. | Cooper, Richard S. | Danesh, John | Dedoussis, George | de Faire, Ulf | Feranil, Alan B. | Ferrières, Jean | Ferrucci, Luigi | Freimer, Nelson B. | Gieger, Christian | Groop, Leif C. | Gudnason, Vilmundur | Gyllensten, Ulf | Hamsten, Anders | Harris, Tamara B. | Hingorani, Aroon | Hirschhorn, Joel N. | Hofman, Albert | Hovingh, G. Kees | Hsiung, Chao Agnes | Humphries, Steve E. | Hunt, Steven C. | Hveem, Kristian | Iribarren, Carlos | Järvelin, Marjo-Riitta | Jula, Antti | Kähönen, Mika | Kaprio, Jaakko | Kesäniemi, Antero | Kivimaki, Mika | Kooner, Jaspal S. | Koudstaal, Peter J. | Krauss, Ronald M. | Kuh, Diana | Kuusisto, Johanna | Kyvik, Kirsten O. | Laakso, Markku | Lakka, Timo A. | Lind, Lars | Lindgren, Cecilia M. | Martin, Nicholas G. | März, Winfried | McCarthy, Mark I. | McKenzie, Colin A. | Meneton, Pierre | Metspalu, Andres | Moilanen, Leena | Morris, Andrew D. | Munroe, Patricia B. | Njølstad, Inger | Pedersen, Nancy L. | Power, Chris | Pramstaller, Peter P. | Price, Jackie F. | Psaty, Bruce M. | Quertermous, Thomas | Rauramaa, Rainer | Saleheen, Danish | Salomaa, Veikko | Sanghera, Dharambir K. | Saramies, Jouko | Schwarz, Peter E.H. | Sheu, Wayne H-H | Shuldiner, Alan R. | Siegbahn, Agneta | Spector, Tim D. | Stefansson, Kari | Strachan, David P. | Tayo, Bamidele O. | Tremoli, Elena | Tuomilehto, Jaakko | Uusitupa, Matti | van Duijn, Cornelia M. | Vollenweider, Peter | Wallentin, Lars | Wareham, Nicholas J. | Whitfield, John B. | Wolffenbuttel, Bruce H.R. | Ordovas, Jose M. | Boerwinkle, Eric | Palmer, Colin N.A. | Thorsteinsdottir, Unnur | Chasman, Daniel I. | Rotter, Jerome I. | Franks, Paul W. | Ripatti, Samuli | Cupples, L. Adrienne | Sandhu, Manjinder S. | Rich, Stephen S. | Boehnke, Michael | Deloukas, Panos | Kathiresan, Sekar | Mohlke, Karen L. | Ingelsson, Erik | Abecasis, Gonçalo R.
Nature genetics  2013;45(11):10.1038/ng.2797.
Low-density lipoprotein (LDL) cholesterol, high-density lipoprotein (HDL) cholesterol, triglycerides, and total cholesterol are heritable, modifiable, risk factors for coronary artery disease. To identify new loci and refine known loci influencing these lipids, we examined 188,578 individuals using genome-wide and custom genotyping arrays. We identify and annotate 157 loci associated with lipid levels at P < 5×10−8, including 62 loci not previously associated with lipid levels in humans. Using dense genotyping in individuals of European, East Asian, South Asian, and African ancestry, we narrow association signals in 12 loci. We find that loci associated with blood lipids are often associated with cardiovascular and metabolic traits including coronary artery disease, type 2 diabetes, blood pressure, waist-hip ratio, and body mass index. Our results illustrate the value of genetic data from individuals of diverse ancestries and provide insights into biological mechanisms regulating blood lipids to guide future genetic, biological, and therapeutic research.
doi:10.1038/ng.2797
PMCID: PMC3838666  PMID: 24097068
4.  Common variants associated with plasma triglycerides and risk for coronary artery disease 
Do, Ron | Willer, Cristen J. | Schmidt, Ellen M. | Sengupta, Sebanti | Gao, Chi | Peloso, Gina M. | Gustafsson, Stefan | Kanoni, Stavroula | Ganna, Andrea | Chen, Jin | Buchkovich, Martin L. | Mora, Samia | Beckmann, Jacques S. | Bragg-Gresham, Jennifer L. | Chang, Hsing-Yi | Demirkan, Ayşe | Den Hertog, Heleen M. | Donnelly, Louise A. | Ehret, Georg B. | Esko, Tõnu | Feitosa, Mary F. | Ferreira, Teresa | Fischer, Krista | Fontanillas, Pierre | Fraser, Ross M. | Freitag, Daniel F. | Gurdasani, Deepti | Heikkilä, Kauko | Hyppönen, Elina | Isaacs, Aaron | Jackson, Anne U. | Johansson, Åsa | Johnson, Toby | Kaakinen, Marika | Kettunen, Johannes | Kleber, Marcus E. | Li, Xiaohui | Luan, Jian'an | Lyytikäinen, Leo-Pekka | Magnusson, Patrik K.E. | Mangino, Massimo | Mihailov, Evelin | Montasser, May E. | Müller-Nurasyid, Martina | Nolte, Ilja M. | O'Connell, Jeffrey R. | Palmer, Cameron D. | Perola, Markus | Petersen, Ann-Kristin | Sanna, Serena | Saxena, Richa | Service, Susan K. | Shah, Sonia | Shungin, Dmitry | Sidore, Carlo | Song, Ci | Strawbridge, Rona J. | Surakka, Ida | Tanaka, Toshiko | Teslovich, Tanya M. | Thorleifsson, Gudmar | Van den Herik, Evita G. | Voight, Benjamin F. | Volcik, Kelly A. | Waite, Lindsay L. | Wong, Andrew | Wu, Ying | Zhang, Weihua | Absher, Devin | Asiki, Gershim | Barroso, Inês | Been, Latonya F. | Bolton, Jennifer L. | Bonnycastle, Lori L | Brambilla, Paolo | Burnett, Mary S. | Cesana, Giancarlo | Dimitriou, Maria | Doney, Alex S.F. | Döring, Angela | Elliott, Paul | Epstein, Stephen E. | Eyjolfsson, Gudmundur Ingi | Gigante, Bruna | Goodarzi, Mark O. | Grallert, Harald | Gravito, Martha L. | Groves, Christopher J. | Hallmans, Göran | Hartikainen, Anna-Liisa | Hayward, Caroline | Hernandez, Dena | Hicks, Andrew A. | Holm, Hilma | Hung, Yi-Jen | Illig, Thomas | Jones, Michelle R. | Kaleebu, Pontiano | Kastelein, John J.P. | Khaw, Kay-Tee | Kim, Eric | Klopp, Norman | Komulainen, Pirjo | Kumari, Meena | Langenberg, Claudia | Lehtimäki, Terho | Lin, Shih-Yi | Lindström, Jaana | Loos, Ruth J.F. | Mach, François | McArdle, Wendy L | Meisinger, Christa | Mitchell, Braxton D. | Müller, Gabrielle | Nagaraja, Ramaiah | Narisu, Narisu | Nieminen, Tuomo V.M. | Nsubuga, Rebecca N. | Olafsson, Isleifur | Ong, Ken K. | Palotie, Aarno | Papamarkou, Theodore | Pomilla, Cristina | Pouta, Anneli | Rader, Daniel J. | Reilly, Muredach P. | Ridker, Paul M. | Rivadeneira, Fernando | Rudan, Igor | Ruokonen, Aimo | Samani, Nilesh | Scharnagl, Hubert | Seeley, Janet | Silander, Kaisa | Stančáková, Alena | Stirrups, Kathleen | Swift, Amy J. | Tiret, Laurence | Uitterlinden, Andre G. | van Pelt, L. Joost | Vedantam, Sailaja | Wainwright, Nicholas | Wijmenga, Cisca | Wild, Sarah H. | Willemsen, Gonneke | Wilsgaard, Tom | Wilson, James F. | Young, Elizabeth H. | Zhao, Jing Hua | Adair, Linda S. | Arveiler, Dominique | Assimes, Themistocles L. | Bandinelli, Stefania | Bennett, Franklyn | Bochud, Murielle | Boehm, Bernhard O. | Boomsma, Dorret I. | Borecki, Ingrid B. | Bornstein, Stefan R. | Bovet, Pascal | Burnier, Michel | Campbell, Harry | Chakravarti, Aravinda | Chambers, John C. | Chen, Yii-Der Ida | Collins, Francis S. | Cooper, Richard S. | Danesh, John | Dedoussis, George | de Faire, Ulf | Feranil, Alan B. | Ferrières, Jean | Ferrucci, Luigi | Freimer, Nelson B. | Gieger, Christian | Groop, Leif C. | Gudnason, Vilmundur | Gyllensten, Ulf | Hamsten, Anders | Harris, Tamara B. | Hingorani, Aroon | Hirschhorn, Joel N. | Hofman, Albert | Hovingh, G. Kees | Hsiung, Chao Agnes | Humphries, Steve E. | Hunt, Steven C. | Hveem, Kristian | Iribarren, Carlos | Järvelin, Marjo-Riitta | Jula, Antti | Kähönen, Mika | Kaprio, Jaakko | Kesäniemi, Antero | Kivimaki, Mika | Kooner, Jaspal S. | Koudstaal, Peter J. | Krauss, Ronald M. | Kuh, Diana | Kuusisto, Johanna | Kyvik, Kirsten O. | Laakso, Markku | Lakka, Timo A. | Lind, Lars | Lindgren, Cecilia M. | Martin, Nicholas G. | März, Winfried | McCarthy, Mark I. | McKenzie, Colin A. | Meneton, Pierre | Metspalu, Andres | Moilanen, Leena | Morris, Andrew D. | Munroe, Patricia B. | Njølstad, Inger | Pedersen, Nancy L. | Power, Chris | Pramstaller, Peter P. | Price, Jackie F. | Psaty, Bruce M. | Quertermous, Thomas | Rauramaa, Rainer | Saleheen, Danish | Salomaa, Veikko | Sanghera, Dharambir K. | Saramies, Jouko | Schwarz, Peter E.H. | Sheu, Wayne H-H | Shuldiner, Alan R. | Siegbahn, Agneta | Spector, Tim D. | Stefansson, Kari | Strachan, David P. | Tayo, Bamidele O. | Tremoli, Elena | Tuomilehto, Jaakko | Uusitupa, Matti | van Duijn, Cornelia M. | Vollenweider, Peter | Wallentin, Lars | Wareham, Nicholas J. | Whitfield, John B. | Wolffenbuttel, Bruce H.R. | Altshuler, David | Ordovas, Jose M. | Boerwinkle, Eric | Palmer, Colin N.A. | Thorsteinsdottir, Unnur | Chasman, Daniel I. | Rotter, Jerome I. | Franks, Paul W. | Ripatti, Samuli | Cupples, L. Adrienne | Sandhu, Manjinder S. | Rich, Stephen S. | Boehnke, Michael | Deloukas, Panos | Mohlke, Karen L. | Ingelsson, Erik | Abecasis, Goncalo R. | Daly, Mark J. | Neale, Benjamin M. | Kathiresan, Sekar
Nature genetics  2013;45(11):1345-1352.
Triglycerides are transported in plasma by specific triglyceride-rich lipoproteins; in epidemiologic studies, increased triglyceride levels correlate with higher risk for coronary artery disease (CAD). However, it is unclear whether this association reflects causal processes. We used 185 common variants recently mapped for plasma lipids (P<5×10−8 for each) to examine the role of triglycerides on risk for CAD. First, we highlight loci associated with both low-density lipoprotein cholesterol (LDL-C) and triglycerides, and show that the direction and magnitude of both are factors in determining CAD risk. Second, we consider loci with only a strong magnitude of association with triglycerides and show that these loci are also associated with CAD. Finally, in a model accounting for effects on LDL-C and/or high-density lipoprotein cholesterol, a polymorphism's strength of effect on triglycerides is correlated with the magnitude of its effect on CAD risk. These results suggest that triglyceride-rich lipoproteins causally influence risk for CAD.
doi:10.1038/ng.2795
PMCID: PMC3904346  PMID: 24097064
5.  Meta-Analysis Investigating Associations Between Healthy Diet and Fasting Glucose and Insulin Levels and Modification by Loci Associated With Glucose Homeostasis in Data From 15 Cohorts 
American Journal of Epidemiology  2012;177(2):103-115.
Whether loci that influence fasting glucose (FG) and fasting insulin (FI) levels, as identified by genome-wide association studies, modify associations of diet with FG or FI is unknown. We utilized data from 15 US and European cohort studies comprising 51,289 persons without diabetes to test whether genotype and diet interact to influence FG or FI concentration. We constructed a diet score using study-specific quartile rankings for intakes of whole grains, fish, fruits, vegetables, and nuts/seeds (favorable) and red/processed meats, sweets, sugared beverages, and fried potatoes (unfavorable). We used linear regression within studies, followed by inverse-variance-weighted meta-analysis, to quantify 1) associations of diet score with FG and FI levels and 2) interactions of diet score with 16 FG-associated loci and 2 FI-associated loci. Diet score (per unit increase) was inversely associated with FG (β = −0.004 mmol/L, 95% confidence interval: −0.005, −0.003) and FI (β = −0.008 ln-pmol/L, 95% confidence interval: −0.009, −0.007) levels after adjustment for demographic factors, lifestyle, and body mass index. Genotype variation at the studied loci did not modify these associations. Healthier diets were associated with lower FG and FI concentrations regardless of genotype at previously replicated FG- and FI-associated loci. Studies focusing on genomic regions that do not yield highly statistically significant associations from main-effect genome-wide association studies may be more fruitful in identifying diet-gene interactions.
doi:10.1093/aje/kws297
PMCID: PMC3707424  PMID: 23255780
diabetes; dietary pattern; gene-environment interaction; glucose; insulin
6.  Mapping cis- and trans-regulatory effects across multiple tissues in twins 
Nature genetics  2012;44(10):1084-1089.
Sequence-based variation in gene expression is a key driver of disease risk. Common variants regulating expression in cis have been mapped in many eQTL studies typically in single tissues from unrelated individuals. Here, we present a comprehensive analysis of gene expression across multiple tissues conducted in a large set of mono- and dizygotic twins that allows systematic dissection of genetic (cis and trans) and non-genetic effects on gene expression. Using identity-by-descent estimates, we show that at least 40% of the total heritable cis-effect on expression cannot be accounted for by common cis-variants, a finding which exposes the contribution of low frequency and rare regulatory variants with respect to both transcriptional regulation and complex trait susceptibility. We show that a substantial proportion of gene expression heritability is trans to the structural gene and identify several replicating trans-variants which act predominantly in a tissue-restricted manner and may regulate the transcription of many genes.
doi:10.1038/ng.2394
PMCID: PMC3784328  PMID: 22941192
7.  Genome-wide association study in people of South Asian ancestry identifies six novel susceptibility loci for type 2 diabetes 
Nature genetics  2011;43(10):984-989.
We carried out a genome wide association study of type-2 diabetes (T2D) amongst 20,119 people of South Asian ancestry (5,561 with T2D); we identified 20 independent SNPs associated with T2D at P<10−4 for testing amongst a further 38,568 South Asians (13,170 with T2D). In combined analysis, common genetic variants at six novel loci (GRB14, ST6GAL1, VPS26A, HMG20A, AP3S2 and HNF4A) were associated with T2D (P=4.1×10−8 to P=1.9×10−11); SNPs at GRB14 were also associated with insulin sensitivity, and at ST6GAL1 and HNF4A with pancreatic beta-cell function respectively. Our findings provide additional insight into mechanisms underlying T2D, and demonstrate the potential for new discovery from genetic association studies in South Asians who have increased susceptibility to T2D.
doi:10.1038/ng.921
PMCID: PMC3773920  PMID: 21874001
8.  A genome-wide approach accounting for body mass index identifies genetic variants influencing fasting glycemic traits and insulin resistance 
Manning, Alisa K. | Hivert, Marie-France | Scott, Robert A. | Grimsby, Jonna L. | Bouatia-Naji, Nabila | Chen, Han | Rybin, Denis | Liu, Ching-Ti | Bielak, Lawrence F. | Prokopenko, Inga | Amin, Najaf | Barnes, Daniel | Cadby, Gemma | Hottenga, Jouke-Jan | Ingelsson, Erik | Jackson, Anne U. | Johnson, Toby | Kanoni, Stavroula | Ladenvall, Claes | Lagou, Vasiliki | Lahti, Jari | Lecoeur, Cecile | Liu, Yongmei | Martinez-Larrad, Maria Teresa | Montasser, May E. | Navarro, Pau | Perry, John R. B. | Rasmussen-Torvik, Laura J. | Salo, Perttu | Sattar, Naveed | Shungin, Dmitry | Strawbridge, Rona J. | Tanaka, Toshiko | van Duijn, Cornelia M. | An, Ping | de Andrade, Mariza | Andrews, Jeanette S. | Aspelund, Thor | Atalay, Mustafa | Aulchenko, Yurii | Balkau, Beverley | Bandinelli, Stefania | Beckmann, Jacques S. | Beilby, John P. | Bellis, Claire | Bergman, Richard N. | Blangero, John | Boban, Mladen | Boehnke, Michael | Boerwinkle, Eric | Bonnycastle, Lori L. | Boomsma, Dorret I. | Borecki, Ingrid B. | Böttcher, Yvonne | Bouchard, Claude | Brunner, Eric | Budimir, Danijela | Campbell, Harry | Carlson, Olga | Chines, Peter S. | Clarke, Robert | Collins, Francis S. | Corbatón-Anchuelo, Arturo | Couper, David | de Faire, Ulf | Dedoussis, George V | Deloukas, Panos | Dimitriou, Maria | Egan, Josephine M | Eiriksdottir, Gudny | Erdos, Michael R. | Eriksson, Johan G. | Eury, Elodie | Ferrucci, Luigi | Ford, Ian | Forouhi, Nita G. | Fox, Caroline S | Franzosi, Maria Grazia | Franks, Paul W | Frayling, Timothy M | Froguel, Philippe | Galan, Pilar | de Geus, Eco | Gigante, Bruna | Glazer, Nicole L. | Goel, Anuj | Groop, Leif | Gudnason, Vilmundur | Hallmans, Göran | Hamsten, Anders | Hansson, Ola | Harris, Tamara B. | Hayward, Caroline | Heath, Simon | Hercberg, Serge | Hicks, Andrew A. | Hingorani, Aroon | Hofman, Albert | Hui, Jennie | Hung, Joseph | Jarvelin, Marjo Riitta | Jhun, Min A. | Johnson, Paul C.D. | Jukema, J Wouter | Jula, Antti | Kao, W.H. | Kaprio, Jaakko | Kardia, Sharon L. R. | Keinanen-Kiukaanniemi, Sirkka | Kivimaki, Mika | Kolcic, Ivana | Kovacs, Peter | Kumari, Meena | Kuusisto, Johanna | Kyvik, Kirsten Ohm | Laakso, Markku | Lakka, Timo | Lannfelt, Lars | Lathrop, G Mark | Launer, Lenore J. | Leander, Karin | Li, Guo | Lind, Lars | Lindstrom, Jaana | Lobbens, Stéphane | Loos, Ruth J. F. | Luan, Jian’an | Lyssenko, Valeriya | Mägi, Reedik | Magnusson, Patrik K. E. | Marmot, Michael | Meneton, Pierre | Mohlke, Karen L. | Mooser, Vincent | Morken, Mario A. | Miljkovic, Iva | Narisu, Narisu | O’Connell, Jeff | Ong, Ken K. | Oostra, Ben A. | Palmer, Lyle J. | Palotie, Aarno | Pankow, James S. | Peden, John F. | Pedersen, Nancy L. | Pehlic, Marina | Peltonen, Leena | Penninx, Brenda | Pericic, Marijana | Perola, Markus | Perusse, Louis | Peyser, Patricia A | Polasek, Ozren | Pramstaller, Peter P. | Province, Michael A. | Räikkönen, Katri | Rauramaa, Rainer | Rehnberg, Emil | Rice, Ken | Rotter, Jerome I. | Rudan, Igor | Ruokonen, Aimo | Saaristo, Timo | Sabater-Lleal, Maria | Salomaa, Veikko | Savage, David B. | Saxena, Richa | Schwarz, Peter | Seedorf, Udo | Sennblad, Bengt | Serrano-Rios, Manuel | Shuldiner, Alan R. | Sijbrands, Eric J.G. | Siscovick, David S. | Smit, Johannes H. | Small, Kerrin S. | Smith, Nicholas L. | Smith, Albert Vernon | Stančáková, Alena | Stirrups, Kathleen | Stumvoll, Michael | Sun, Yan V. | Swift, Amy J. | Tönjes, Anke | Tuomilehto, Jaakko | Trompet, Stella | Uitterlinden, Andre G. | Uusitupa, Matti | Vikström, Max | Vitart, Veronique | Vohl, Marie-Claude | Voight, Benjamin F. | Vollenweider, Peter | Waeber, Gerard | Waterworth, Dawn M | Watkins, Hugh | Wheeler, Eleanor | Widen, Elisabeth | Wild, Sarah H. | Willems, Sara M. | Willemsen, Gonneke | Wilson, James F. | Witteman, Jacqueline C.M. | Wright, Alan F. | Yaghootkar, Hanieh | Zelenika, Diana | Zemunik, Tatijana | Zgaga, Lina | Wareham, Nicholas J. | McCarthy, Mark I. | Barroso, Ines | Watanabe, Richard M. | Florez, Jose C. | Dupuis, Josée | Meigs, James B. | Langenberg, Claudia
Nature genetics  2012;44(6):659-669.
Recent genome-wide association studies have described many loci implicated in type 2 diabetes (T2D) pathophysiology and beta-cell dysfunction, but contributed little to our understanding of the genetic basis of insulin resistance. We hypothesized that genes implicated in insulin resistance pathways may be uncovered by accounting for differences in body mass index (BMI) and potential interaction between BMI and genetic variants. We applied a novel joint meta-analytical approach to test associations with fasting insulin (FI) and glucose (FG) on a genome-wide scale. We present six previously unknown FI loci at P<5×10−8 in combined discovery and follow-up analyses of 52 studies comprising up to 96,496non-diabetic individuals. Risk variants were associated with higher triglyceride and lower HDL cholesterol levels, suggestive of a role for these FI loci in insulin resistance pathways. The localization of these additional loci will aid further characterization of the role of insulin resistance in T2D pathophysiology.
doi:10.1038/ng.2274
PMCID: PMC3613127  PMID: 22581228
9.  Large-scale association analyses identify new loci influencing glycemic traits and provide insight into the underlying biological pathways 
Scott, Robert A | Lagou, Vasiliki | Welch, Ryan P | Wheeler, Eleanor | Montasser, May E | Luan, Jian’an | Mägi, Reedik | Strawbridge, Rona J | Rehnberg, Emil | Gustafsson, Stefan | Kanoni, Stavroula | Rasmussen-Torvik, Laura J | Yengo, Loïc | Lecoeur, Cecile | Shungin, Dmitry | Sanna, Serena | Sidore, Carlo | Johnson, Paul C D | Jukema, J Wouter | Johnson, Toby | Mahajan, Anubha | Verweij, Niek | Thorleifsson, Gudmar | Hottenga, Jouke-Jan | Shah, Sonia | Smith, Albert V | Sennblad, Bengt | Gieger, Christian | Salo, Perttu | Perola, Markus | Timpson, Nicholas J | Evans, David M | Pourcain, Beate St | Wu, Ying | Andrews, Jeanette S | Hui, Jennie | Bielak, Lawrence F | Zhao, Wei | Horikoshi, Momoko | Navarro, Pau | Isaacs, Aaron | O’Connell, Jeffrey R | Stirrups, Kathleen | Vitart, Veronique | Hayward, Caroline | Esko, Tönu | Mihailov, Evelin | Fraser, Ross M | Fall, Tove | Voight, Benjamin F | Raychaudhuri, Soumya | Chen, Han | Lindgren, Cecilia M | Morris, Andrew P | Rayner, Nigel W | Robertson, Neil | Rybin, Denis | Liu, Ching-Ti | Beckmann, Jacques S | Willems, Sara M | Chines, Peter S | Jackson, Anne U | Kang, Hyun Min | Stringham, Heather M | Song, Kijoung | Tanaka, Toshiko | Peden, John F | Goel, Anuj | Hicks, Andrew A | An, Ping | Müller-Nurasyid, Martina | Franco-Cereceda, Anders | Folkersen, Lasse | Marullo, Letizia | Jansen, Hanneke | Oldehinkel, Albertine J | Bruinenberg, Marcel | Pankow, James S | North, Kari E | Forouhi, Nita G | Loos, Ruth J F | Edkins, Sarah | Varga, Tibor V | Hallmans, Göran | Oksa, Heikki | Antonella, Mulas | Nagaraja, Ramaiah | Trompet, Stella | Ford, Ian | Bakker, Stephan J L | Kong, Augustine | Kumari, Meena | Gigante, Bruna | Herder, Christian | Munroe, Patricia B | Caulfield, Mark | Antti, Jula | Mangino, Massimo | Small, Kerrin | Miljkovic, Iva | Liu, Yongmei | Atalay, Mustafa | Kiess, Wieland | James, Alan L | Rivadeneira, Fernando | Uitterlinden, Andre G | Palmer, Colin N A | Doney, Alex S F | Willemsen, Gonneke | Smit, Johannes H | Campbell, Susan | Polasek, Ozren | Bonnycastle, Lori L | Hercberg, Serge | Dimitriou, Maria | Bolton, Jennifer L | Fowkes, Gerard R | Kovacs, Peter | Lindström, Jaana | Zemunik, Tatijana | Bandinelli, Stefania | Wild, Sarah H | Basart, Hanneke V | Rathmann, Wolfgang | Grallert, Harald | Maerz, Winfried | Kleber, Marcus E | Boehm, Bernhard O | Peters, Annette | Pramstaller, Peter P | Province, Michael A | Borecki, Ingrid B | Hastie, Nicholas D | Rudan, Igor | Campbell, Harry | Watkins, Hugh | Farrall, Martin | Stumvoll, Michael | Ferrucci, Luigi | Waterworth, Dawn M | Bergman, Richard N | Collins, Francis S | Tuomilehto, Jaakko | Watanabe, Richard M | de Geus, Eco J C | Penninx, Brenda W | Hofman, Albert | Oostra, Ben A | Psaty, Bruce M | Vollenweider, Peter | Wilson, James F | Wright, Alan F | Hovingh, G Kees | Metspalu, Andres | Uusitupa, Matti | Magnusson, Patrik K E | Kyvik, Kirsten O | Kaprio, Jaakko | Price, Jackie F | Dedoussis, George V | Deloukas, Panos | Meneton, Pierre | Lind, Lars | Boehnke, Michael | Shuldiner, Alan R | van Duijn, Cornelia M | Morris, Andrew D | Toenjes, Anke | Peyser, Patricia A | Beilby, John P | Körner, Antje | Kuusisto, Johanna | Laakso, Markku | Bornstein, Stefan R | Schwarz, Peter E H | Lakka, Timo A | Rauramaa, Rainer | Adair, Linda S | Smith, George Davey | Spector, Tim D | Illig, Thomas | de Faire, Ulf | Hamsten, Anders | Gudnason, Vilmundur | Kivimaki, Mika | Hingorani, Aroon | Keinanen-Kiukaanniemi, Sirkka M | Saaristo, Timo E | Boomsma, Dorret I | Stefansson, Kari | van der Harst, Pim | Dupuis, Josée | Pedersen, Nancy L | Sattar, Naveed | Harris, Tamara B | Cucca, Francesco | Ripatti, Samuli | Salomaa, Veikko | Mohlke, Karen L | Balkau, Beverley | Froguel, Philippe | Pouta, Anneli | Jarvelin, Marjo-Riitta | Wareham, Nicholas J | Bouatia-Naji, Nabila | McCarthy, Mark I | Franks, Paul W | Meigs, James B | Teslovich, Tanya M | Florez, Jose C | Langenberg, Claudia | Ingelsson, Erik | Prokopenko, Inga | Barroso, Inês
Nature genetics  2012;44(9):991-1005.
Through genome-wide association meta-analyses of up to 133,010 individuals of European ancestry without diabetes, including individuals newly genotyped using the Metabochip, we have raised the number of confirmed loci influencing glycemic traits to 53, of which 33 also increase type 2 diabetes risk (q < 0.05). Loci influencing fasting insulin showed association with lipid levels and fat distribution, suggesting impact on insulin resistance. Gene-based analyses identified further biologically plausible loci, suggesting that additional loci beyond those reaching genome-wide significance are likely to represent real associations. This conclusion is supported by an excess of directionally consistent and nominally significant signals between discovery and follow-up studies. Functional follow-up of these newly discovered loci will further improve our understanding of glycemic control.
doi:10.1038/ng.2385
PMCID: PMC3433394  PMID: 22885924
10.  Large-scale association analysis provides insights into the genetic architecture and pathophysiology of type 2 diabetes 
Morris, Andrew P | Voight, Benjamin F | Teslovich, Tanya M | Ferreira, Teresa | Segrè, Ayellet V | Steinthorsdottir, Valgerdur | Strawbridge, Rona J | Khan, Hassan | Grallert, Harald | Mahajan, Anubha | Prokopenko, Inga | Kang, Hyun Min | Dina, Christian | Esko, Tonu | Fraser, Ross M | Kanoni, Stavroula | Kumar, Ashish | Lagou, Vasiliki | Langenberg, Claudia | Luan, Jian'an | Lindgren, Cecilia M | Müller-Nurasyid, Martina | Pechlivanis, Sonali | Rayner, N William | Scott, Laura J | Wiltshire, Steven | Yengo, Loic | Kinnunen, Leena | Rossin, Elizabeth J | Raychaudhuri, Soumya | Johnson, Andrew D | Dimas, Antigone S | Loos, Ruth J F | Vedantam, Sailaja | Chen, Han | Florez, Jose C | Fox, Caroline | Liu, Ching-Ti | Rybin, Denis | Couper, David J | Kao, Wen Hong L | Li, Man | Cornelis, Marilyn C | Kraft, Peter | Sun, Qi | van Dam, Rob M | Stringham, Heather M | Chines, Peter S | Fischer, Krista | Fontanillas, Pierre | Holmen, Oddgeir L | Hunt, Sarah E | Jackson, Anne U | Kong, Augustine | Lawrence, Robert | Meyer, Julia | Perry, John RB | Platou, Carl GP | Potter, Simon | Rehnberg, Emil | Robertson, Neil | Sivapalaratnam, Suthesh | Stančáková, Alena | Stirrups, Kathleen | Thorleifsson, Gudmar | Tikkanen, Emmi | Wood, Andrew R | Almgren, Peter | Atalay, Mustafa | Benediktsson, Rafn | Bonnycastle, Lori L | Burtt, Noël | Carey, Jason | Charpentier, Guillaume | Crenshaw, Andrew T | Doney, Alex S F | Dorkhan, Mozhgan | Edkins, Sarah | Emilsson, Valur | Eury, Elodie | Forsen, Tom | Gertow, Karl | Gigante, Bruna | Grant, George B | Groves, Christopher J | Guiducci, Candace | Herder, Christian | Hreidarsson, Astradur B | Hui, Jennie | James, Alan | Jonsson, Anna | Rathmann, Wolfgang | Klopp, Norman | Kravic, Jasmina | Krjutškov, Kaarel | Langford, Cordelia | Leander, Karin | Lindholm, Eero | Lobbens, Stéphane | Männistö, Satu | Mirza, Ghazala | Mühleisen, Thomas W | Musk, Bill | Parkin, Melissa | Rallidis, Loukianos | Saramies, Jouko | Sennblad, Bengt | Shah, Sonia | Sigurðsson, Gunnar | Silveira, Angela | Steinbach, Gerald | Thorand, Barbara | Trakalo, Joseph | Veglia, Fabrizio | Wennauer, Roman | Winckler, Wendy | Zabaneh, Delilah | Campbell, Harry | van Duijn, Cornelia | Uitterlinden89-, Andre G | Hofman, Albert | Sijbrands, Eric | Abecasis, Goncalo R | Owen, Katharine R | Zeggini, Eleftheria | Trip, Mieke D | Forouhi, Nita G | Syvänen, Ann-Christine | Eriksson, Johan G | Peltonen, Leena | Nöthen, Markus M | Balkau, Beverley | Palmer, Colin N A | Lyssenko, Valeriya | Tuomi, Tiinamaija | Isomaa, Bo | Hunter, David J | Qi, Lu | Shuldiner, Alan R | Roden, Michael | Barroso, Ines | Wilsgaard, Tom | Beilby, John | Hovingh, Kees | Price, Jackie F | Wilson, James F | Rauramaa, Rainer | Lakka, Timo A | Lind, Lars | Dedoussis, George | Njølstad, Inger | Pedersen, Nancy L | Khaw, Kay-Tee | Wareham, Nicholas J | Keinanen-Kiukaanniemi, Sirkka M | Saaristo, Timo E | Korpi-Hyövälti, Eeva | Saltevo, Juha | Laakso, Markku | Kuusisto, Johanna | Metspalu, Andres | Collins, Francis S | Mohlke, Karen L | Bergman, Richard N | Tuomilehto, Jaakko | Boehm, Bernhard O | Gieger, Christian | Hveem, Kristian | Cauchi, Stephane | Froguel, Philippe | Baldassarre, Damiano | Tremoli, Elena | Humphries, Steve E | Saleheen, Danish | Danesh, John | Ingelsson, Erik | Ripatti, Samuli | Salomaa, Veikko | Erbel, Raimund | Jöckel, Karl-Heinz | Moebus, Susanne | Peters, Annette | Illig, Thomas | de Faire, Ulf | Hamsten, Anders | Morris, Andrew D | Donnelly, Peter J | Frayling, Timothy M | Hattersley, Andrew T | Boerwinkle, Eric | Melander, Olle | Kathiresan, Sekar | Nilsson, Peter M | Deloukas, Panos | Thorsteinsdottir, Unnur | Groop, Leif C | Stefansson, Kari | Hu, Frank | Pankow, James S | Dupuis, Josée | Meigs, James B | Altshuler, David | Boehnke, Michael | McCarthy, Mark I
Nature genetics  2012;44(9):981-990.
To extend understanding of the genetic architecture and molecular basis of type 2 diabetes (T2D), we conducted a meta-analysis of genetic variants on the Metabochip involving 34,840 cases and 114,981 controls, overwhelmingly of European descent. We identified ten previously unreported T2D susceptibility loci, including two demonstrating sex-differentiated association. Genome-wide analyses of these data are consistent with a long tail of further common variant loci explaining much of the variation in susceptibility to T2D. Exploration of the enlarged set of susceptibility loci implicates several processes, including CREBBP-related transcription, adipocytokine signalling and cell cycle regulation, in diabetes pathogenesis.
doi:10.1038/ng.2383
PMCID: PMC3442244  PMID: 22885922
11.  The Presence of Methylation Quantitative Trait Loci Indicates a Direct Genetic Influence on the Level of DNA Methylation in Adipose Tissue 
PLoS ONE  2013;8(2):e55923.
Genetic variants that associate with DNA methylation at CpG sites (methylation quantitative trait loci, meQTLs) offer a potential biological mechanism of action for disease associated SNPs. We investigated whether meQTLs exist in abdominal subcutaneous adipose tissue (SAT) and if CpG methylation associates with metabolic syndrome (MetSyn) phenotypes. We profiled 27,718 genomic regions in abdominal SAT samples of 38 unrelated individuals using differential methylation hybridization (DMH) together with genotypes at 5,227,243 SNPs and expression of 17,209 mRNA transcripts. Validation and replication of significant meQTLs was pursued in an independent cohort of 181 female twins. We find that, at 5% false discovery rate, methylation levels of 149 DMH regions associate with at least one SNP in a ±500 kilobase cis-region in our primary study. We sought to validate 19 of these in the replication study and find that five of these significantly associate with the corresponding meQTL SNPs from the primary study. We find that none of the 149 meQTL top SNPs is a significant expression quantitative trait locus in our expression data, but we observed association between expression levels of two mRNA transcripts and cis-methylation status. Our results indicate that DNA CpG methylation in abdominal SAT is partly under genetic control. This study provides a starting point for future investigations of DNA methylation in adipose tissue.
doi:10.1371/journal.pone.0055923
PMCID: PMC3576415  PMID: 23431366
12.  Large-scale association analysis provides insights into the genetic architecture and pathophysiology of type 2 diabetes 
Morris, Andrew P | Voight, Benjamin F | Teslovich, Tanya M | Ferreira, Teresa | Segré, Ayellet V | Steinthorsdottir, Valgerdur | Strawbridge, Rona J | Khan, Hassan | Grallert, Harald | Mahajan, Anubha | Prokopenko, Inga | Kang, Hyun Min | Dina, Christian | Esko, Tonu | Fraser, Ross M | Kanoni, Stavroula | Kumar, Ashish | Lagou, Vasiliki | Langenberg, Claudia | Luan, Jian’an | Lindgren, Cecilia M | Müller-Nurasyid, Martina | Pechlivanis, Sonali | Rayner, N William | Scott, Laura J | Wiltshire, Steven | Yengo, Loic | Kinnunen, Leena | Rossin, Elizabeth J | Raychaudhuri, Soumya | Johnson, Andrew D | Dimas, Antigone S | Loos, Ruth J F | Vedantam, Sailaja | Chen, Han | Florez, Jose C | Fox, Caroline | Liu, Ching-Ti | Rybin, Denis | Couper, David J | Kao, Wen Hong L | Li, Man | Cornelis, Marilyn C | Kraft, Peter | Sun, Qi | van Dam, Rob M | Stringham, Heather M | Chines, Peter S | Fischer, Krista | Fontanillas, Pierre | Holmen, Oddgeir L | Hunt, Sarah E | Jackson, Anne U | Kong, Augustine | Lawrence, Robert | Meyer, Julia | Perry, John R B | Platou, Carl G P | Potter, Simon | Rehnberg, Emil | Robertson, Neil | Sivapalaratnam, Suthesh | Stančáková, Alena | Stirrups, Kathleen | Thorleifsson, Gudmar | Tikkanen, Emmi | Wood, Andrew R | Almgren, Peter | Atalay, Mustafa | Benediktsson, Rafn | Bonnycastle, Lori L | Burtt, Noël | Carey, Jason | Charpentier, Guillaume | Crenshaw, Andrew T | Doney, Alex S F | Dorkhan, Mozhgan | Edkins, Sarah | Emilsson, Valur | Eury, Elodie | Forsen, Tom | Gertow, Karl | Gigante, Bruna | Grant, George B | Groves, Christopher J | Guiducci, Candace | Herder, Christian | Hreidarsson, Astradur B | Hui, Jennie | James, Alan | Jonsson, Anna | Rathmann, Wolfgang | Klopp, Norman | Kravic, Jasmina | Krjutškov, Kaarel | Langford, Cordelia | Leander, Karin | Lindholm, Eero | Lobbens, Stéphane | Männistö, Satu | Mirza, Ghazala | Mühleisen, Thomas W | Musk, Bill | Parkin, Melissa | Rallidis, Loukianos | Saramies, Jouko | Sennblad, Bengt | Shah, Sonia | Sigurðsson, Gunnar | Silveira, Angela | Steinbach, Gerald | Thorand, Barbara | Trakalo, Joseph | Veglia, Fabrizio | Wennauer, Roman | Winckler, Wendy | Zabaneh, Delilah | Campbell, Harry | van Duijn, Cornelia | Uitterlinden, Andre G | Hofman, Albert | Sijbrands, Eric | Abecasis, Goncalo R | Owen, Katharine R | Zeggini, Eleftheria | Trip, Mieke D | Forouhi, Nita G | Syvänen, Ann-Christine | Eriksson, Johan G | Peltonen, Leena | Nöthen, Markus M | Balkau, Beverley | Palmer, Colin N A | Lyssenko, Valeriya | Tuomi, Tiinamaija | Isomaa, Bo | Hunter, David J | Qi, Lu | Shuldiner, Alan R | Roden, Michael | Barroso, Ines | Wilsgaard, Tom | Beilby, John | Hovingh, Kees | Price, Jackie F | Wilson, James F | Rauramaa, Rainer | Lakka, Timo A | Lind, Lars | Dedoussis, George | Njølstad, Inger | Pedersen, Nancy L | Khaw, Kay-Tee | Wareham, Nicholas J | Keinanen-Kiukaanniemi, Sirkka M | Saaristo, Timo E | Korpi-Hyövälti, Eeva | Saltevo, Juha | Laakso, Markku | Kuusisto, Johanna | Metspalu, Andres | Collins, Francis S | Mohlke, Karen L | Bergman, Richard N | Tuomilehto, Jaakko | Boehm, Bernhard O | Gieger, Christian | Hveem, Kristian | Cauchi, Stephane | Froguel, Philippe | Baldassarre, Damiano | Tremoli, Elena | Humphries, Steve E | Saleheen, Danish | Danesh, John | Ingelsson, Erik | Ripatti, Samuli | Salomaa, Veikko | Erbel, Raimund | Jöckel, Karl-Heinz | Moebus, Susanne | Peters, Annette | Illig, Thomas | de Faire, Ulf | Hamsten, Anders | Morris, Andrew D | Donnelly, Peter J | Frayling, Timothy M | Hattersley, Andrew T | Boerwinkle, Eric | Melander, Olle | Kathiresan, Sekar | Nilsson, Peter M | Deloukas, Panos | Thorsteinsdottir, Unnur | Groop, Leif C | Stefansson, Kari | Hu, Frank | Pankow, James S | Dupuis, Josée | Meigs, James B | Altshuler, David | Boehnke, Michael | McCarthy, Mark I
Nature genetics  2012;44(9):981-990.
To extend understanding of the genetic architecture and molecular basis of type 2 diabetes (T2D), we conducted a meta-analysis of genetic variants on the Metabochip involving 34,840 cases and 114,981 controls, overwhelmingly of European descent. We identified ten previously unreported T2D susceptibility loci, including two demonstrating sex-differentiated association. Genome-wide analyses of these data are consistent with a long tail of further common variant loci explaining much of the variation in susceptibility to T2D. Exploration of the enlarged set of susceptibility loci implicates several processes, including CREBBP-related transcription, adipocytokine signalling and cell cycle regulation, in diabetes pathogenesis.
doi:10.1038/ng.2383
PMCID: PMC3442244  PMID: 22885922
13.  Variants in MTNR1B influence fasting glucose levels 
Prokopenko, Inga | Langenberg, Claudia | Florez, Jose C | Saxena, Richa | Soranzo, Nicole | Thorleifsson, Gudmar | Loos, Ruth J F | Manning, Alisa K | Jackson, Anne U | Aulchenko, Yurii | Potter, Simon C | Erdos, Michael R | Sanna, Serena | Hottenga, Jouke-Jan | Wheeler, Eleanor | Kaakinen, Marika | Lyssenko, Valeriya | Chen, Wei-Min | Ahmadi, Kourosh | Beckmann, Jacques S | Bergman, Richard N | Bochud, Murielle | Bonnycastle, Lori L | Buchanan, Thomas A | Cao, Antonio | Cervino, Alessandra | Coin, Lachlan | Collins, Francis S | Crisponi, Laura | de Geus, Eco J C | Dehghan, Abbas | Deloukas, Panos | Doney, Alex S F | Elliott, Paul | Freimer, Nelson | Gateva, Vesela | Herder, Christian | Hofman, Albert | Hughes, Thomas E | Hunt, Sarah | Illig, Thomas | Inouye, Michael | Isomaa, Bo | Johnson, Toby | Kong, Augustine | Krestyaninova, Maria | Kuusisto, Johanna | Laakso, Markku | Lim, Noha | Lindblad, Ulf | Lindgren, Cecilia M | McCann, Owen T | Mohlke, Karen L | Morris, Andrew D | Naitza, Silvia | Orrù, Marco | Palmer, Colin N A | Pouta, Anneli | Randall, Joshua | Rathmann, Wolfgang | Saramies, Jouko | Scheet, Paul | Scott, Laura J | Scuteri, Angelo | Sharp, Stephen | Sijbrands, Eric | Smit, Jan H | Song, Kijoung | Steinthorsdottir, Valgerdur | Stringham, Heather M | Tuomi, Tiinamaija | Tuomilehto, Jaakko | Uitterlinden, André G | Voight, Benjamin F | Waterworth, Dawn | Wichmann, H-Erich | Willemsen, Gonneke | Witteman, Jacqueline C M | Yuan, Xin | Zhao, Jing Hua | Zeggini, Eleftheria | Schlessinger, David | Sandhu, Manjinder | Boomsma, Dorret I | Uda, Manuela | Spector, Tim D | Penninx, Brenda WJH | Altshuler, David | Vollenweider, Peter | Jarvelin, Marjo Riitta | Lakatta, Edward | Waeber, Gerard | Fox, Caroline S | Peltonen, Leena | Groop, Leif C | Mooser, Vincent | Cupples, L Adrienne | Thorsteinsdottir, Unnur | Boehnke, Michael | Barroso, Inês | Van Duijn, Cornelia | Dupuis, Josée | Watanabe, Richard M | Stefansson, Kari | McCarthy, Mark I | Wareham, Nicholas J | Meigs, James B | Abecasis, Gonçalo R
Nature genetics  2008;41(1):77-81.
To identify previously unknown genetic loci associated with fasting glucose concentrations, we examined the leading association signals in ten genome-wide association scans involving a total of 36,610 individuals of European descent. Variants in the gene encoding melatonin receptor 1B (MTNR1B) were consistently associated with fasting glucose across all ten studies. The strongest signal was observed at rs10830963, where each G allele (frequency 0.30 in HapMap CEU) was associated with an increase of 0.07 (95% CI = 0.06-0.08) mmol/l in fasting glucose levels (P = 3.2 = × 10−50) and reduced beta-cell function as measured by homeostasis model assessment (HOMA-B, P = 1.1 × 10−15). The same allele was associated with an increased risk of type 2 diabetes (odds ratio = 1.09 (1.05-1.12), per G allele P = 3.3 × 10−7) in a meta-analysis of 13 case-control studies totaling 18,236 cases and 64,453 controls. Our analyses also confirm previous associations of fasting glucose with variants at the G6PC2 (rs560887, P = 1.1 × 10−57) and GCK (rs4607517, P = 1.0 × 10−25) loci.
doi:10.1038/ng.290
PMCID: PMC2682768  PMID: 19060907
14.  Genome-Wide Association Identifies Nine Common Variants Associated With Fasting Proinsulin Levels and Provides New Insights Into the Pathophysiology of Type 2 Diabetes 
Strawbridge, Rona J. | Dupuis, Josée | Prokopenko, Inga | Barker, Adam | Ahlqvist, Emma | Rybin, Denis | Petrie, John R. | Travers, Mary E. | Bouatia-Naji, Nabila | Dimas, Antigone S. | Nica, Alexandra | Wheeler, Eleanor | Chen, Han | Voight, Benjamin F. | Taneera, Jalal | Kanoni, Stavroula | Peden, John F. | Turrini, Fabiola | Gustafsson, Stefan | Zabena, Carina | Almgren, Peter | Barker, David J.P. | Barnes, Daniel | Dennison, Elaine M. | Eriksson, Johan G. | Eriksson, Per | Eury, Elodie | Folkersen, Lasse | Fox, Caroline S. | Frayling, Timothy M. | Goel, Anuj | Gu, Harvest F. | Horikoshi, Momoko | Isomaa, Bo | Jackson, Anne U. | Jameson, Karen A. | Kajantie, Eero | Kerr-Conte, Julie | Kuulasmaa, Teemu | Kuusisto, Johanna | Loos, Ruth J.F. | Luan, Jian'an | Makrilakis, Konstantinos | Manning, Alisa K. | Martínez-Larrad, María Teresa | Narisu, Narisu | Nastase Mannila, Maria | Öhrvik, John | Osmond, Clive | Pascoe, Laura | Payne, Felicity | Sayer, Avan A. | Sennblad, Bengt | Silveira, Angela | Stančáková, Alena | Stirrups, Kathy | Swift, Amy J. | Syvänen, Ann-Christine | Tuomi, Tiinamaija | van 't Hooft, Ferdinand M. | Walker, Mark | Weedon, Michael N. | Xie, Weijia | Zethelius, Björn | Ongen, Halit | Mälarstig, Anders | Hopewell, Jemma C. | Saleheen, Danish | Chambers, John | Parish, Sarah | Danesh, John | Kooner, Jaspal | Östenson, Claes-Göran | Lind, Lars | Cooper, Cyrus C. | Serrano-Ríos, Manuel | Ferrannini, Ele | Forsen, Tom J. | Clarke, Robert | Franzosi, Maria Grazia | Seedorf, Udo | Watkins, Hugh | Froguel, Philippe | Johnson, Paul | Deloukas, Panos | Collins, Francis S. | Laakso, Markku | Dermitzakis, Emmanouil T. | Boehnke, Michael | McCarthy, Mark I. | Wareham, Nicholas J. | Groop, Leif | Pattou, François | Gloyn, Anna L. | Dedoussis, George V. | Lyssenko, Valeriya | Meigs, James B. | Barroso, Inês | Watanabe, Richard M. | Ingelsson, Erik | Langenberg, Claudia | Hamsten, Anders | Florez, Jose C.
Diabetes  2011;60(10):2624-2634.
OBJECTIVE
Proinsulin is a precursor of mature insulin and C-peptide. Higher circulating proinsulin levels are associated with impaired β-cell function, raised glucose levels, insulin resistance, and type 2 diabetes (T2D). Studies of the insulin processing pathway could provide new insights about T2D pathophysiology.
RESEARCH DESIGN AND METHODS
We have conducted a meta-analysis of genome-wide association tests of ∼2.5 million genotyped or imputed single nucleotide polymorphisms (SNPs) and fasting proinsulin levels in 10,701 nondiabetic adults of European ancestry, with follow-up of 23 loci in up to 16,378 individuals, using additive genetic models adjusted for age, sex, fasting insulin, and study-specific covariates.
RESULTS
Nine SNPs at eight loci were associated with proinsulin levels (P < 5 × 10−8). Two loci (LARP6 and SGSM2) have not been previously related to metabolic traits, one (MADD) has been associated with fasting glucose, one (PCSK1) has been implicated in obesity, and four (TCF7L2, SLC30A8, VPS13C/C2CD4A/B, and ARAP1, formerly CENTD2) increase T2D risk. The proinsulin-raising allele of ARAP1 was associated with a lower fasting glucose (P = 1.7 × 10−4), improved β-cell function (P = 1.1 × 10−5), and lower risk of T2D (odds ratio 0.88; P = 7.8 × 10−6). Notably, PCSK1 encodes the protein prohormone convertase 1/3, the first enzyme in the insulin processing pathway. A genotype score composed of the nine proinsulin-raising alleles was not associated with coronary disease in two large case-control datasets.
CONCLUSIONS
We have identified nine genetic variants associated with fasting proinsulin. Our findings illuminate the biology underlying glucose homeostasis and T2D development in humans and argue against a direct role of proinsulin in coronary artery disease pathogenesis.
doi:10.2337/db11-0415
PMCID: PMC3178302  PMID: 21873549
15.  The Metabochip, a Custom Genotyping Array for Genetic Studies of Metabolic, Cardiovascular, and Anthropometric Traits 
PLoS Genetics  2012;8(8):e1002793.
Genome-wide association studies have identified hundreds of loci for type 2 diabetes, coronary artery disease and myocardial infarction, as well as for related traits such as body mass index, glucose and insulin levels, lipid levels, and blood pressure. These studies also have pointed to thousands of loci with promising but not yet compelling association evidence. To establish association at additional loci and to characterize the genome-wide significant loci by fine-mapping, we designed the “Metabochip,” a custom genotyping array that assays nearly 200,000 SNP markers. Here, we describe the Metabochip and its component SNP sets, evaluate its performance in capturing variation across the allele-frequency spectrum, describe solutions to methodological challenges commonly encountered in its analysis, and evaluate its performance as a platform for genotype imputation. The metabochip achieves dramatic cost efficiencies compared to designing single-trait follow-up reagents, and provides the opportunity to compare results across a range of related traits. The metabochip and similar custom genotyping arrays offer a powerful and cost-effective approach to follow-up large-scale genotyping and sequencing studies and advance our understanding of the genetic basis of complex human diseases and traits.
Author Summary
Recent genetic studies have identified hundreds of regions of the human genome that contribute to risk for type 2 diabetes, coronary artery disease and myocardial infarction, and to related quantitative traits such as body mass index, glucose and insulin levels, blood lipid levels, and blood pressure. These results motivate two central questions: (1) can further genetic investigation identify additional associated regions?; and (2) can more detailed genetic investigation help us identify the causal variants (or variants more strongly correlated with the causal variants) in the regions identified so far? Addressing these questions requires assaying many genetic variants in DNA samples from thousands of individuals, which is expensive and timeconsuming when done a few SNPs at a time. To facilitate these investigations, we designed the “Metabochip,” a custom genotyping array that assays variation in nearly 200,000 sites in the human genome. Here we describe the Metabochip, evaluate its performance in assaying human genetic variation, and describe solutions to methodological challenges commonly encountered in its analysis.
doi:10.1371/journal.pgen.1002793
PMCID: PMC3410907  PMID: 22876189
16.  A genome-wide association meta-analysis identifies new childhood obesity loci 
Bradfield, Jonathan P. | Taal, H. Rob | Timpson, Nicholas J. | Scherag, André | Lecoeur, Cecile | Warrington, Nicole M. | Hypponen, Elina | Holst, Claus | Valcarcel, Beatriz | Thiering, Elisabeth | Salem, Rany M. | Schumacher, Fredrick R. | Cousminer, Diana L. | Sleiman, Patrick M.A. | Zhao, Jianhua | Berkowitz, Robert I. | Vimaleswaran, Karani S. | Jarick, Ivonne | Pennell, Craig E. | Evans, David M. | St. Pourcain, Beate | Berry, Diane J. | Mook-Kanamori, Dennis O | Hofman, Albert | Rivadeinera, Fernando | Uitterlinden, André G. | van Duijn, Cornelia M. | van der Valk, Ralf J.P. | de Jongste, Johan C. | Postma, Dirkje S. | Boomsma, Dorret I. | Gauderman, William J. | Hassanein, Mohamed T. | Lindgren, Cecilia M. | Mägi, Reedik | Boreham, Colin A.G. | Neville, Charlotte E. | Moreno, Luis A. | Elliott, Paul | Pouta, Anneli | Hartikainen, Anna-Liisa | Li, Mingyao | Raitakari, Olli | Lehtimäki, Terho | Eriksson, Johan G. | Palotie, Aarno | Dallongeville, Jean | Das, Shikta | Deloukas, Panos | McMahon, George | Ring, Susan M. | Kemp, John P. | Buxton, Jessica L. | Blakemore, Alexandra I.F. | Bustamante, Mariona | Guxens, Mònica | Hirschhorn, Joel N. | Gillman, Matthew W. | Kreiner-Møller, Eskil | Bisgaard, Hans | Gilliland, Frank D. | Heinrich, Joachim | Wheeler, Eleanor | Barroso, Inês | O'Rahilly, Stephen | Meirhaeghe, Aline | Sørensen, Thorkild I.A. | Power, Chris | Palmer, Lyle J. | Hinney, Anke | Widen, Elisabeth | Farooqi, I. Sadaf | McCarthy, Mark I. | Froguel, Philippe | Meyre, David | Hebebrand, Johannes | Jarvelin, Marjo-Riitta | Jaddoe, Vincent W.V. | Smith, George Davey | Hakonarson, Hakon | Grant, Struan F.A.
Nature Genetics  2012;44(5):526-531.
Multiple genetic variants have been associated with adult obesity and a few with severe obesity in childhood; however, less progress has been made to establish genetic influences on common early-onset obesity. We performed a North American-Australian-European collaborative meta-analysis of fourteen studies consisting of 5,530 cases (≥95th percentile of body mass index (BMI)) and 8,318 controls (<50th percentile of BMI) of European ancestry. Taking forward the eight novel signals yielding association with P < 5×10−6 in to nine independent datasets (n = 2,818 cases and 4,083 controls) we observed two loci that yielded a genome wide significant combined P-value, namely near OLFM4 on 13q14 (rs9568856; P=1.82×10−9; OR=1.22) and within HOXB5 on 17q21 (rs9299; P=3.54×10−9; OR=1.14). Both loci continued to show association when including two extreme childhood obesity cohorts (n = 2,214 cases and 2,674 controls). Finally, these two loci yielded directionally consistent associations in the GIANT meta-analysis of adult BMI1.
doi:10.1038/ng.2247
PMCID: PMC3370100  PMID: 22484627
17.  Association of Genetic Loci With Glucose Levels in Childhood and Adolescence 
Diabetes  2011;60(6):1805-1812.
OBJECTIVE
To investigate whether associations of common genetic variants recently identified for fasting glucose or insulin levels in nondiabetic adults are detectable in healthy children and adolescents.
RESEARCH DESIGN AND METHODS
A total of 16 single nucleotide polymorphisms (SNPs) associated with fasting glucose were genotyped in six studies of children and adolescents of European origin, including over 6,000 boys and girls aged 9–16 years. We performed meta-analyses to test associations of individual SNPs and a weighted risk score of the 16 loci with fasting glucose.
RESULTS
Nine loci were associated with glucose levels in healthy children and adolescents, with four of these associations reported in previous studies and five reported here for the first time (GLIS3, PROX1, SLC2A2, ADCY5, and CRY2). Effect sizes were similar to those in adults, suggesting age-independent effects of these fasting glucose loci. Children and adolescents carrying glucose-raising alleles of G6PC2, MTNR1B, GCK, and GLIS3 also showed reduced β-cell function, as indicated by homeostasis model assessment of β-cell function. Analysis using a weighted risk score showed an increase [β (95% CI)] in fasting glucose level of 0.026 mmol/L (0.021–0.031) for each unit increase in the score.
CONCLUSIONS
Novel fasting glucose loci identified in genome-wide association studies of adults are associated with altered fasting glucose levels in healthy children and adolescents with effect sizes comparable to adults. In nondiabetic adults, fasting glucose changes little over time, and our results suggest that age-independent effects of fasting glucose loci contribute to long-term interindividual differences in glucose levels from childhood onwards.
doi:10.2337/db10-1575
PMCID: PMC3114379  PMID: 21515849
18.  Extent, Causes, and Consequences of Small RNA Expression Variation in Human Adipose Tissue 
PLoS Genetics  2012;8(5):e1002704.
Small RNAs are functional molecules that modulate mRNA transcripts and have been implicated in the aetiology of several common diseases. However, little is known about the extent of their variability within the human population. Here, we characterise the extent, causes, and effects of naturally occurring variation in expression and sequence of small RNAs from adipose tissue in relation to genotype, gene expression, and metabolic traits in the MuTHER reference cohort. We profiled the expression of 15 to 30 base pair RNA molecules in subcutaneous adipose tissue from 131 individuals using high-throughput sequencing, and quantified levels of 591 microRNAs and small nucleolar RNAs. We identified three genetic variants and three RNA editing events. Highly expressed small RNAs are more conserved within mammals than average, as are those with highly variable expression. We identified 14 genetic loci significantly associated with nearby small RNA expression levels, seven of which also regulate an mRNA transcript level in the same region. In addition, these loci are enriched for variants significant in genome-wide association studies for body mass index. Contrary to expectation, we found no evidence for negative correlation between expression level of a microRNA and its target mRNAs. Trunk fat mass, body mass index, and fasting insulin were associated with more than twenty small RNA expression levels each, while fasting glucose had no significant associations. This study highlights the similar genetic complexity and shared genetic control of small RNA and mRNA transcripts, and gives a quantitative picture of small RNA expression variation in the human population.
Author Summary
Genetic information is transmitted to the cell only through RNA molecules. A special class of RNAs is comprised of the small (up to 30 nucleotide) ones, known to be potent regulators of various cellular processes. At the same time, they have not been as widely studied as messenger RNAs—we do not know how much variation in their sequence and expression level occurs naturally in human populations or how this variability influences other traits. We measured small RNA levels and genetic variability in fat tissue from 131 individuals by high-throughput sequencing. We could associate the expression levels with genetic background of the individuals, as well as changes in metabolic traits. Surprisingly, we found no large scale influence of small RNA variation on mRNA levels, their main regulatory target. Overall, our study is the first to give a quantitative picture of the naturally occurring variation in these important regulatory molecules in human fat tissue.
doi:10.1371/journal.pgen.1002704
PMCID: PMC3349731  PMID: 22589741
19.  Epigenome-Wide Scans Identify Differentially Methylated Regions for Age and Age-Related Phenotypes in a Healthy Ageing Population 
PLoS Genetics  2012;8(4):e1002629.
Age-related changes in DNA methylation have been implicated in cellular senescence and longevity, yet the causes and functional consequences of these variants remain unclear. To elucidate the role of age-related epigenetic changes in healthy ageing and potential longevity, we tested for association between whole-blood DNA methylation patterns in 172 female twins aged 32 to 80 with age and age-related phenotypes. Twin-based DNA methylation levels at 26,690 CpG-sites showed evidence for mean genome-wide heritability of 18%, which was supported by the identification of 1,537 CpG-sites with methylation QTLs in cis at FDR 5%. We performed genome-wide analyses to discover differentially methylated regions (DMRs) for sixteen age-related phenotypes (ap-DMRs) and chronological age (a-DMRs). Epigenome-wide association scans (EWAS) identified age-related phenotype DMRs (ap-DMRs) associated with LDL (STAT5A), lung function (WT1), and maternal longevity (ARL4A, TBX20). In contrast, EWAS for chronological age identified hundreds of predominantly hyper-methylated age DMRs (490 a-DMRs at FDR 5%), of which only one (TBX20) was also associated with an age-related phenotype. Therefore, the majority of age-related changes in DNA methylation are not associated with phenotypic measures of healthy ageing in later life. We replicated a large proportion of a-DMRs in a sample of 44 younger adult MZ twins aged 20 to 61, suggesting that a-DMRs may initiate at an earlier age. We next explored potential genetic and environmental mechanisms underlying a-DMRs and ap-DMRs. Genome-wide overlap across cis-meQTLs, genotype-phenotype associations, and EWAS ap-DMRs identified CpG-sites that had cis-meQTLs with evidence for genotype–phenotype association, where the CpG-site was also an ap-DMR for the same phenotype. Monozygotic twin methylation difference analyses identified one potential environmentally-mediated ap-DMR associated with total cholesterol and LDL (CSMD1). Our results suggest that in a small set of genes DNA methylation may be a candidate mechanism of mediating not only environmental, but also genetic effects on age-related phenotypes.
Author Summary
Epigenetic patterns vary during healthy ageing and development. Age-related DNA methylation changes have been implicated in cellular senescence and longevity, yet the causes and functional consequences of these variants remain unclear. To understand the biological mechanisms involved in potential longevity and rate of healthy ageing, we performed genome-wide association of epigenetic and genetic variation with both chronological age and age-related phenotypes. We identified hundreds of DNA methylation variants significantly associated with age and replicated these in an independent sample of young adult twins. Only a small proportion of these variants were also associated with age-related phenotypes. Therefore, the majority of age-related epigenetic changes do not contribute to rate of healthy ageing at later stages in life. Our results suggest that age-related changes in methylation occur throughout an individual's lifespan and that a proportion of these may be initiated from an early age. Intriguingly, a fraction of the age differentially methylated regions also associated with genetic variants in our sample, suggesting that DNA methylation may be a candidate mechanism of mediating not only environmental but also genetic effects on age-related phenotypes.
doi:10.1371/journal.pgen.1002629
PMCID: PMC3330116  PMID: 22532803
20.  Identification of an imprinted master trans-regulator at the KLF14 locus related to multiple metabolic phenotypes 
Nature genetics  2011;43(6):561-564.
Genome-wide association studies have identified many genetic variants associated with complex traits. However, at only a minority of loci have the molecular mechanisms mediating these associations been characterized. In parallel, whilst cis-regulatory patterns of gene expression have been extensively explored, the identification of trans-regulatory effects in humans has attracted less attention. We demonstrate that the Type 2 diabetes and HDL-cholesterol associated cis-acting eQTL of the maternally-expressed transcription factor KLF14 acts as a master trans-regulator of adipose gene expression. Expression levels of genes regulated by this trans-eQTL are highly-correlated with concurrently-measured metabolic traits, and a subset of the trans-genes harbor variants directly-associated with metabolic phenotypes. This trans-eQTL network provides a mechanistic understanding of the effect of the KLF14 locus on metabolic disease risk, providing a potential model for other complex traits.
doi:10.1038/ng.833
PMCID: PMC3192952  PMID: 21572415
21.  Genome-wide meta-analysis identifies 11 new loci for anthropometric traits and provides insights into genetic architecture 
Berndt, Sonja I. | Gustafsson, Stefan | Mägi, Reedik | Ganna, Andrea | Wheeler, Eleanor | Feitosa, Mary F. | Justice, Anne E. | Monda, Keri L. | Croteau-Chonka, Damien C. | Day, Felix R. | Esko, Tõnu | Fall, Tove | Ferreira, Teresa | Gentilini, Davide | Jackson, Anne U. | Luan, Jian’an | Randall, Joshua C. | Vedantam, Sailaja | Willer, Cristen J. | Winkler, Thomas W. | Wood, Andrew R. | Workalemahu, Tsegaselassie | Hu, Yi-Juan | Lee, Sang Hong | Liang, Liming | Lin, Dan-Yu | Min, Josine L. | Neale, Benjamin M. | Thorleifsson, Gudmar | Yang, Jian | Albrecht, Eva | Amin, Najaf | Bragg-Gresham, Jennifer L. | Cadby, Gemma | den Heijer, Martin | Eklund, Niina | Fischer, Krista | Goel, Anuj | Hottenga, Jouke-Jan | Huffman, Jennifer E. | Jarick, Ivonne | Johansson, Åsa | Johnson, Toby | Kanoni, Stavroula | Kleber, Marcus E. | König, Inke R. | Kristiansson, Kati | Kutalik, Zoltán | Lamina, Claudia | Lecoeur, Cecile | Li, Guo | Mangino, Massimo | McArdle, Wendy L. | Medina-Gomez, Carolina | Müller-Nurasyid, Martina | Ngwa, Julius S. | Nolte, Ilja M. | Paternoster, Lavinia | Pechlivanis, Sonali | Perola, Markus | Peters, Marjolein J. | Preuss, Michael | Rose, Lynda M. | Shi, Jianxin | Shungin, Dmitry | Smith, Albert Vernon | Strawbridge, Rona J. | Surakka, Ida | Teumer, Alexander | Trip, Mieke D. | Tyrer, Jonathan | Van Vliet-Ostaptchouk, Jana V. | Vandenput, Liesbeth | Waite, Lindsay L. | Zhao, Jing Hua | Absher, Devin | Asselbergs, Folkert W. | Atalay, Mustafa | Attwood, Antony P. | Balmforth, Anthony J. | Basart, Hanneke | Beilby, John | Bonnycastle, Lori L. | Brambilla, Paolo | Bruinenberg, Marcel | Campbell, Harry | Chasman, Daniel I. | Chines, Peter S. | Collins, Francis S. | Connell, John M. | Cookson, William | de Faire, Ulf | de Vegt, Femmie | Dei, Mariano | Dimitriou, Maria | Edkins, Sarah | Estrada, Karol | Evans, David M. | Farrall, Martin | Ferrario, Marco M. | Ferrières, Jean | Franke, Lude | Frau, Francesca | Gejman, Pablo V. | Grallert, Harald | Grönberg, Henrik | Gudnason, Vilmundur | Hall, Alistair S. | Hall, Per | Hartikainen, Anna-Liisa | Hayward, Caroline | Heard-Costa, Nancy L. | Heath, Andrew C. | Hebebrand, Johannes | Homuth, Georg | Hu, Frank B. | Hunt, Sarah E. | Hyppönen, Elina | Iribarren, Carlos | Jacobs, Kevin B. | Jansson, John-Olov | Jula, Antti | Kähönen, Mika | Kathiresan, Sekar | Kee, Frank | Khaw, Kay-Tee | Kivimaki, Mika | Koenig, Wolfgang | Kraja, Aldi T. | Kumari, Meena | Kuulasmaa, Kari | Kuusisto, Johanna | Laitinen, Jaana H. | Lakka, Timo A. | Langenberg, Claudia | Launer, Lenore J. | Lind, Lars | Lindström, Jaana | Liu, Jianjun | Liuzzi, Antonio | Lokki, Marja-Liisa | Lorentzon, Mattias | Madden, Pamela A. | Magnusson, Patrik K. | Manunta, Paolo | Marek, Diana | März, Winfried | Mateo Leach, Irene | McKnight, Barbara | Medland, Sarah E. | Mihailov, Evelin | Milani, Lili | Montgomery, Grant W. | Mooser, Vincent | Mühleisen, Thomas W. | Munroe, Patricia B. | Musk, Arthur W. | Narisu, Narisu | Navis, Gerjan | Nicholson, George | Nohr, Ellen A. | Ong, Ken K. | Oostra, Ben A. | Palmer, Colin N.A. | Palotie, Aarno | Peden, John F. | Pedersen, Nancy | Peters, Annette | Polasek, Ozren | Pouta, Anneli | Pramstaller, Peter P. | Prokopenko, Inga | Pütter, Carolin | Radhakrishnan, Aparna | Raitakari, Olli | Rendon, Augusto | Rivadeneira, Fernando | Rudan, Igor | Saaristo, Timo E. | Sambrook, Jennifer G. | Sanders, Alan R. | Sanna, Serena | Saramies, Jouko | Schipf, Sabine | Schreiber, Stefan | Schunkert, Heribert | Shin, So-Youn | Signorini, Stefano | Sinisalo, Juha | Skrobek, Boris | Soranzo, Nicole | Stančáková, Alena | Stark, Klaus | Stephens, Jonathan C. | Stirrups, Kathleen | Stolk, Ronald P. | Stumvoll, Michael | Swift, Amy J. | Theodoraki, Eirini V. | Thorand, Barbara | Tregouet, David-Alexandre | Tremoli, Elena | Van der Klauw, Melanie M. | van Meurs, Joyce B.J. | Vermeulen, Sita H. | Viikari, Jorma | Virtamo, Jarmo | Vitart, Veronique | Waeber, Gérard | Wang, Zhaoming | Widén, Elisabeth | Wild, Sarah H. | Willemsen, Gonneke | Winkelmann, Bernhard R. | Witteman, Jacqueline C.M. | Wolffenbuttel, Bruce H.R. | Wong, Andrew | Wright, Alan F. | Zillikens, M. Carola | Amouyel, Philippe | Boehm, Bernhard O. | Boerwinkle, Eric | Boomsma, Dorret I. | Caulfield, Mark J. | Chanock, Stephen J. | Cupples, L. Adrienne | Cusi, Daniele | Dedoussis, George V. | Erdmann, Jeanette | Eriksson, Johan G. | Franks, Paul W. | Froguel, Philippe | Gieger, Christian | Gyllensten, Ulf | Hamsten, Anders | Harris, Tamara B. | Hengstenberg, Christian | Hicks, Andrew A. | Hingorani, Aroon | Hinney, Anke | Hofman, Albert | Hovingh, Kees G. | Hveem, Kristian | Illig, Thomas | Jarvelin, Marjo-Riitta | Jöckel, Karl-Heinz | Keinanen-Kiukaanniemi, Sirkka M. | Kiemeney, Lambertus A. | Kuh, Diana | Laakso, Markku | Lehtimäki, Terho | Levinson, Douglas F. | Martin, Nicholas G. | Metspalu, Andres | Morris, Andrew D. | Nieminen, Markku S. | Njølstad, Inger | Ohlsson, Claes | Oldehinkel, Albertine J. | Ouwehand, Willem H. | Palmer, Lyle J. | Penninx, Brenda | Power, Chris | Province, Michael A. | Psaty, Bruce M. | Qi, Lu | Rauramaa, Rainer | Ridker, Paul M. | Ripatti, Samuli | Salomaa, Veikko | Samani, Nilesh J. | Snieder, Harold | Sørensen, Thorkild I.A. | Spector, Timothy D. | Stefansson, Kari | Tönjes, Anke | Tuomilehto, Jaakko | Uitterlinden, André G. | Uusitupa, Matti | van der Harst, Pim | Vollenweider, Peter | Wallaschofski, Henri | Wareham, Nicholas J. | Watkins, Hugh | Wichmann, H.-Erich | Wilson, James F. | Abecasis, Goncalo R. | Assimes, Themistocles L. | Barroso, Inês | Boehnke, Michael | Borecki, Ingrid B. | Deloukas, Panos | Fox, Caroline S. | Frayling, Timothy | Groop, Leif C. | Haritunian, Talin | Heid, Iris M. | Hunter, David | Kaplan, Robert C. | Karpe, Fredrik | Moffatt, Miriam | Mohlke, Karen L. | O’Connell, Jeffrey R. | Pawitan, Yudi | Schadt, Eric E. | Schlessinger, David | Steinthorsdottir, Valgerdur | Strachan, David P. | Thorsteinsdottir, Unnur | van Duijn, Cornelia M. | Visscher, Peter M. | Di Blasio, Anna Maria | Hirschhorn, Joel N. | Lindgren, Cecilia M. | Morris, Andrew P. | Meyre, David | Scherag, André | McCarthy, Mark I. | Speliotes, Elizabeth K. | North, Kari E. | Loos, Ruth J.F. | Ingelsson, Erik
Nature genetics  2013;45(5):501-512.
Approaches exploiting extremes of the trait distribution may reveal novel loci for common traits, but it is unknown whether such loci are generalizable to the general population. In a genome-wide search for loci associated with upper vs. lower 5th percentiles of body mass index, height and waist-hip ratio, as well as clinical classes of obesity including up to 263,407 European individuals, we identified four new loci (IGFBP4, H6PD, RSRC1, PPP2R2A) influencing height detected in the tails and seven new loci (HNF4G, RPTOR, GNAT2, MRPS33P4, ADCY9, HS6ST3, ZZZ3) for clinical classes of obesity. Further, we show that there is large overlap in terms of genetic structure and distribution of variants between traits based on extremes and the general population and little etiologic heterogeneity between obesity subgroups.
doi:10.1038/ng.2606
PMCID: PMC3973018  PMID: 23563607
22.  Common variants near ATM are associated with glycemic response to metformin in type 2 diabetes 
Nature genetics  2010;43(2):117-120.
Metformin is the most commonly used pharmacological therapy for type 2 diabetes. We carried out a GWA study on glycaemic response to metformin in 1024 Scottish patients with type 2 diabetes. Replication was in two cohorts consisting of 1783 Scottish patients and 1113 patients from the UK Prospective Diabetes Study. In a meta-analysis (n=3920) we observed an association (P=2.9 *10−9) for a SNP rs11212617 at a locus containing the ataxia telangiectasia mutated (ATM) gene with an odds ratio of 1.35 (95% CI 1.22 to 1.49) for treatment success. In a rat hepatoma cell line, inhibition of ATM with KU-55933 attenuated the phosphorylation and activation of AMPK in response to metformin. We conclude that ATM, a gene known to be involved in DNA repair and cell cycle control, plays a role in the effect of metformin upstream of AMPK, and variation in this gene alters glycaemic response to metformin.
doi:10.1038/ng.735
PMCID: PMC3030919  PMID: 21186350
23.  The Architecture of Gene Regulatory Variation across Multiple Human Tissues: The MuTHER Study 
PLoS Genetics  2011;7(2):e1002003.
While there have been studies exploring regulatory variation in one or more tissues, the complexity of tissue-specificity in multiple primary tissues is not yet well understood. We explore in depth the role of cis-regulatory variation in three human tissues: lymphoblastoid cell lines (LCL), skin, and fat. The samples (156 LCL, 160 skin, 166 fat) were derived simultaneously from a subset of well-phenotyped healthy female twins of the MuTHER resource. We discover an abundance of cis-eQTLs in each tissue similar to previous estimates (858 or 4.7% of genes). In addition, we apply factor analysis (FA) to remove effects of latent variables, thus more than doubling the number of our discoveries (1,822 eQTL genes). The unique study design (Matched Co-Twin Analysis—MCTA) permits immediate replication of eQTLs using co-twins (93%–98%) and validation of the considerable gain in eQTL discovery after FA correction. We highlight the challenges of comparing eQTLs between tissues. After verifying previous significance threshold-based estimates of tissue-specificity, we show their limitations given their dependency on statistical power. We propose that continuous estimates of the proportion of tissue-shared signals and direct comparison of the magnitude of effect on the fold change in expression are essential properties that jointly provide a biologically realistic view of tissue-specificity. Under this framework we demonstrate that 30% of eQTLs are shared among the three tissues studied, while another 29% appear exclusively tissue-specific. However, even among the shared eQTLs, a substantial proportion (10%–20%) have significant differences in the magnitude of fold change between genotypic classes across tissues. Our results underline the need to account for the complexity of eQTL tissue-specificity in an effort to assess consequences of such variants for complex traits.
Author Summary
Regulation of gene expression is a fundamental cellular process determining a large proportion of the phenotypic variance. Previous studies have identified genetic loci influencing gene expression levels (eQTLs), but the complexity of their tissue-specific properties has not yet been well-characterized. In this study, we perform cis-eQTL analysis in a unique matched co-twin design for three human tissues derived simultaneously from the same set of individuals. The study design allows validation of the substantial discoveries we make in each tissue. We explore in depth the tissue-dependent features of regulatory variants and estimate the proportions of shared and specific effects. We use continuous measures of eQTL sharing to circumvent the statistical power limitations of comparing direct overlap of eQTLs in multiple tissues. In this framework, we demonstrate that 30% of eQTLs are shared among tissues, while 29% are exclusively tissue-specific. Furthermore, we show that the fold change in expression between eQTL genotypic classes differs between tissues. Even among shared eQTLs, we report a substantial proportion (10%–20%) of significant tissue differences in magnitude of these effects. The complexities we highlight here are essential for understanding the impact of regulatory variants on complex traits.
doi:10.1371/journal.pgen.1002003
PMCID: PMC3033383  PMID: 21304890
24.  Integrated Genetic and Epigenetic Analysis Identifies Haplotype-Specific Methylation in the FTO Type 2 Diabetes and Obesity Susceptibility Locus 
PLoS ONE  2010;5(11):e14040.
Recent multi-dimensional approaches to the study of complex disease have revealed powerful insights into how genetic and epigenetic factors may underlie their aetiopathogenesis. We examined genotype-epigenotype interactions in the context of Type 2 Diabetes (T2D), focussing on known regions of genomic susceptibility. We assayed DNA methylation in 60 females, stratified according to disease susceptibility haplotype using previously identified association loci. CpG methylation was assessed using methylated DNA immunoprecipitation on a targeted array (MeDIP-chip) and absolute methylation values were estimated using a Bayesian algorithm (BATMAN). Absolute methylation levels were quantified across LD blocks, and we identified increased DNA methylation on the FTO obesity susceptibility haplotype, tagged by the rs8050136 risk allele A (p = 9.40×10−4, permutation p = 1.0×10−3). Further analysis across the 46 kb LD block using sliding windows localised the most significant difference to be within a 7.7 kb region (p = 1.13×10−7). Sequence level analysis, followed by pyrosequencing validation, revealed that the methylation difference was driven by the co-ordinated phase of CpG-creating SNPs across the risk haplotype. This 7.7 kb region of haplotype-specific methylation (HSM), encapsulates a Highly Conserved Non-Coding Element (HCNE) that has previously been validated as a long-range enhancer, supported by the histone H3K4me1 enhancer signature. This study demonstrates that integration of Genome-Wide Association (GWA) SNP and epigenomic DNA methylation data can identify potential novel genotype-epigenotype interactions within disease-associated loci, thus providing a novel route to aid unravelling common complex diseases.
doi:10.1371/journal.pone.0014040
PMCID: PMC2987816  PMID: 21124985
25.  Dissection of the genetics of Parkinson's disease identifies an additional association 5′ of SNCA and multiple associated haplotypes at 17q21 
Human Molecular Genetics  2010;20(2):345-353.
We performed a genome-wide association study (GWAS) in 1705 Parkinson's disease (PD) UK patients and 5175 UK controls, the largest sample size so far for a PD GWAS. Replication was attempted in an additional cohort of 1039 French PD cases and 1984 controls for the 27 regions showing the strongest evidence of association (P< 10−4). We replicated published associations in the 4q22/SNCA and 17q21/MAPT chromosome regions (P< 10−10) and found evidence for an additional independent association in 4q22/SNCA. A detailed analysis of the haplotype structure at 17q21 showed that there are three separate risk groups within this region. We found weak but consistent evidence of association for common variants located in three previously published associated regions (4p15/BST1, 4p16/GAK and 1q32/PARK16). We found no support for the previously reported SNP association in 12q12/LRRK2. We also found an association of the two SNPs in 4q22/SNCA with the age of onset of the disease.
doi:10.1093/hmg/ddq469
PMCID: PMC3005904  PMID: 21044948

Results 1-25 (42)